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Reply To: | Classification, clustering, and phylogeny estimation |
Date: | Tue, 17 Aug 2021 06:50:40 +0000 |
Content-Type: | multipart/alternative |
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?Call For Papers
2nd Workshop on
Incremental classification and clustering, concept drift, novelty detection in big/fast data context (IncrLearn)
https://incrlearn.sciencesconf.org/
In conjunction with
21st IEEE International Conference on Data Mining (ICDM 2021)
December 7-11, 2021, Auckland, New Zealand
?This workshop aims to offer a meeting opportunity for academics and industry-related researchers, belonging to the various communities of Computational Intelligence, Machine Learning, Experimental Design, Data Mining and Big/Fast Data Management to discuss new areas of incremental classification, concept drift management and novelty detection and on their application to analysis of time varying information and huge dataset of various natures. Another important aim of the workshop is to bridge the gap between data acquisition or experimentation and model building.
Through an exhaustive coverage of the incremental learning area workshop will provide fruitful exchanges between plenaries, contributors and workshop attendees. The emerging big/fast data context will be taken into consideration in the workshop.
The set of proposed incremental techniques includes, but is not limited to:
* Novelty detection algorithms and techniques
* Semi-supervised and active learning approaches
* Adaptive hierarchical, k-means or density-based methods
* Adaptive neural methods and associated Hebbian learning techniques
* Incremental deep learning
* Multiview diachronic approaches
* Probabilistic approaches
* Distributed approaches
* Graph partitioning methods and incremental clustering approaches based on attributed graphs
* Incremental clustering approaches based on swarm intelligence and genetic algorithms
* Evolving classifier ensemble techniques
* Incremental classification methods and incremental classifier evaluation
* Dynamic feature selection techniques
* Clustering of time series
* Visualization methods for evolving data analysis results
The list of application domain includes, but it is not limited to:
* Evolving textual information analysis
* Evolving social network analysis
* Dynamic process control and tracking
* Intrusion and anomaly detection
* Genomics and DNA micro-array data analysis
* Adaptive recommender and filtering systems
* Scientometrics, webometrics and technological survey
* Incremental learning in LPWAN and IoT context
Important dates:
* Paper submission: September 3, 2021
* Notification of acceptance: September 24, 2021
* Camera-ready: October 1, 2021
* ICDM 2020 Conference: December 7, 2021
Submission Guidelines:
* Follow the regular submission guidelines of ICDM 2021
?https://www.wi-lab.com/cyberchair/2021/icdm21/scripts/submit.php?subarea=S06&undisplay_detail=1&wh=/cyberchair/2021/icdm21/scripts/ws_submit.php
Paper will be triple blind reviewed. The accepted papers will appear in ICDM workshops proceedings.
Contact Persons (feel free to ask questions):
Jean-Charles Lamirel: [log in to unmask]
Pascal Cuxac: [log in to unmask]
Manuel Roveri: [log in to unmask]
Albert Bifet: [log in to unmask]
Pascal Cuxac
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Head of INIST-CNRS- Text & Data Mining Team
INIST-CNRS
2, rue Jean Zay
CS 10310
54519 Vandoeuvre lès Nancy
France
+33 (0)3 83 50 46 00
https://www.researchgate.net/profile/Pascal_Cuxac
https://sites.google.com/view/pascalcuxac
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